Session F8 (full papers)

In recent transition research issues of place-specificity, multiplicity and the long-term character of system change are increasingly emphasised. After some seminal contributions pointed out the importance of spatial aspects in transitions, many studies have underlined the place-specific character of these processes. In this line, scholars argue to acknowledge the multiplicity of transitions, understood as the variety of possible ways to reconfigure and change a socio-technical system (e.g. mobility, energy). The ways how systems are changed are shaped by place-specific institutional and governance arrangements (Hansen/Coenen 2015, Hodson et al. 2017). The latter has however not been systematically analyzed in empirical studies. It also remains largely hidden how actions of actors on the micro-level impact on organizational and institutional change over time, leading towards sustainability on the system level. Although the long-term character of transitions is frequently highlighted, many studies focus on the initial stage of a transition (Brown et al. 2013, Hansen/Coenen 2015) and thus do not capture the outcome of micro-dynamics at the macro-level of the transition path at later points. How and if changes are stabilized is not considered in depth.

In line with other authors (Brown et al. 2013, Fünfschilling/Truffer 2014, Hansen/Coenen 2015, Geels et al. 2016, Hodson et al. 2017), we argue for a profounder research into (de-)institutionalization processes in sustainability transitions and the actors that drive them on the micro-level. Making these complex processes visible, is a major methodological challenge. Causal mechanisms over time and between multiple regimes often remain unclear in existing case study approaches. Changes in institutional and governance arrangements, which are usually gradual and only add up to more fundamental change over time, are particularly hard to capture. The research question “How can hidden organizational and institutional changes and the underlying micro-dynamics be made visible in systemic transition paths?” therefore drives our paper.

We develop the methodological approach of a transition topology (Strambach/Pflitsch 2017) to enable structured navigation (Köhler et al. 2017) between different levels of analysis. As a research heuristic the actor-centered institutionalism approach (Mayntz/Scharpf 1995, Scharpf 2000) is used. Theoretically our methodological approach is based on neo-institutional organization theory and evolutionary economic geography. The transition topology is a directed graph which captures a system’s transition path across different institutional settings over time in a multi-scalar way. The transition topology displays all important institutional and organizational changes towards sustainability in the system and the connections behind. Institutional changes are operationalized as events in time, which indicate a shift in regulative, normative or cognitive elements (Scott 2001). Organizational changes refer to the establishment of new organizations, which includes more fluid as well as more permanent organizational forms. The topology enables both the analysis of the empirical material and the communication with the scientific community (Langley et al. 2013).

The potential of the transition topology is illustrated using the example of a regional system. The Augsburg region provides a particularly suitable example as the transition process there spans different regimes. The topology shows how gradual changes at an early point in time initiate a dynamic later in time. It makes apparent that institutional settings of different regimes are closely connected and influence each other in their transition dynamic, in particular through boundary spanning actors, hybrid organizational forms and temporary events. The topology makes these “hidden dynamics” visible and it can provide a basis for systematic comparisons of cases. It can be used to establish a typology of transition paths to sustainability at a system level, based on variations in key actors, the nature of their interactions with each other and the organizational dynamics that develop over time.

Sustainability transitions require complex transdisciplinary dialogue processes among different stakeholder groups. When policy options are discussed with decision-makers, scientists often support them with the help of quantitative outputs provided by economic models.  As could be observed in the climate policy processes of the European Union, the choice of model and its design which led to the respective outputs are seldom questioned in policy discussions. Thus, making the model and its parameters transparent and integrating them into stakeholder dialogues is essential for successful and democratic decision-making processes. Furthermore, such an integration allows for the discussion of a broader variety of pathways or scenarios supplied by models. Digital technologies combined with large computing capacity have led to a new methodological frontier through the possibility of interactive visualization of pathways, hence increasing efficiency and impact of stakeholder dialogues in decision-making processes. By describing such a process in light of a mobility transition towards sustainability, we show how an agent based model can be applied to stakeholder discussions among decision-makers. The model, which is a consumer agent-based model (ABM), investigates the diffusion of innovative technologies in social networks. Through the inclusion of individual preferences such as environmental and consumer attitudes as well as financial constraints, agents learn and alter their decisions concerning different mobility modes. By discussing input parameters, model outputs and assumptions about future developments within a broader context of the mobility transition in an iterative process, we establish narratives for an urban sustainable future. The development of these narratives will take place in a “decision theater”, an interactive environment where stakeholders can directly visualize the consequences of their choices. Observing the reactions of the model based on a change of inputs and, thus, gaining insight on the model, will enhance transparency. Moreover, scientists can change their primary role as information providers for policy makers to a co-designed approach that aims to explore future pathways with stakeholders. Hence, this paper can contribute to the stakeholder-model nexus in a threefold way: Firstly, it can serve as a methodological guideline for scientists striving to integrate ABMs and stakeholder dialogues by providing a framework for such interactions. This includes a distinction of dimension of model parameters into those which can be influenced by stakeholders (action) and others that describe events which occur without influence, as well as those that are primarily value-based and those which are mainly technological. Secondly, it can contribute to the effective use of new technologies and data in stakeholder involvement. Thirdly, it can enhance the literature on socio-technical sustainability transitions, with a special focus on future mobility.

The challenge of transforming the energy system

The energy system is undergoing a paradigm shift. So far the grid was a centralized system, dominated by a few large power generation plants and a large-scale distribu-tion of electricity to end-users. The load-flow was pre-determined, and the roles of producers and consumers were clearly defined. However, renewable energy sources (RES) and new low carbon electricity technologies seriously challenge this conventional energy supply system. On the one side, PV, wind and small-scale cogeneration plants are producing electricity and heat in a distributed way. On the other side, end-users are becoming more flexible and are producing their own electricity as well. This transition results in new uncertainties and risks, mainly because electricity generation and consumption will become harder to predict and unforeseen power fluctuations will become more likely. Especially power distribution grids will be facing these situations, since they host a large share of installed RES and constitute the connection point to the end-user [1].

Energy systems as sociotechnical systems

A possible solution to cope with these challenges is the application of new types of collaborative (information) management and governance measures [2]. One important topic in this context is the use of local flexibilities from end-users for grid management issues. Since these flexibilities can also be used for market operations or for ancillary services, there is a need to design a proper framework to organize the use of flexibilities.

Here, if not before, it becomes apparent that the energy system constitutes a socio-technical system that encompasses technical as well as social elements and interactions: Social actors with variable rationality (e.g. trans-mission system operator – TSO, distribution network operator – DNO, energy retailers, and end-users) interact and collaborate within a technical infrastructure system (e.g. through energy purchase/sell, active and reactive power exchange or ancillary services).

Collaborative information management

This paper presents our approach of modelling an interdisciplinary framework for a collaborative information management, which is applied to a power distribution grid and pays particular attention to the emergent, bottom-up behaviour of the power grid. Furthermore, the framework aims at formulating what-if scenarios for future electrical distribution networks, conducting experiments with different system configurations and modes of governance.  The proposed framework is based on design principles of agent-based modelling and simulation (ABMS) as well as a sociological macro-micro-macro-model [3]: Governance measures do not necessarily have a direct impact on the dynamics of a socio-technical system, but rather influence decision-making of strategic actors at the micro-level (e.g. end-users), which then leads to emergent effects on the macro-level (e.g. power-surplus, power-shortage or even blackouts). Consequently, this paper aims to provide a conceptual framework for linking (technical and social) simulation models from electrical engineering and sociology in order to depict such an emergence. As far as the authors’ knowledge is concerned, no previous work deals with collaborative management in power systems, with special focus on distribution grids and end-users, using a socio-technical approach.

References

[1] Järventausta P, Repo S, Rautiainen A, Partanen J (2010) Smart grid power system control in distributed generation environment. Annual Reviews in Control 34(2):277–286. doi:10.1016/j.arcontrol.2010.08.005

[2] Markovic DS, Zivkovic D, Branovic I, Popovic R, Cvetkovic D (2013) Smart power grid and cloud computing. Renewable and Sustainable Energy Reviews 24:566–577. doi:10.1016/j.rser.2013.03.068

[3] Coleman JS (1990) Foundations of Social Theory. Harvard University Press, Cambridge/Mass.